Precision machine vision inspection systems (or “vision systems” for short) can be utilized to obtain precise dimensional measurements of inspected objects and to inspect various other object characteristics. Such systems may include a computer, a camera and optical system, and a precision stage that is movable in multiple directions so as to allow the camera to scan the features of a workpiece that is being inspected. One exemplary prior art system that is commercially available is the QUICK VISION® series of PC-based vision systems and QVPAK® software available from Mitutoyo America Corporation (MAC), located in Aurora, Ill. The features and operation of the QUICK VISION® series of vision systems and the QVPAK® software are generally described, for example, in the QVPAK 3D CNC Vision Measuring Machine User's Guide, published January 2003, and the QVPAK 3D CNC Vision Measuring Machine Operation Guide, published September 1996, each of which is hereby incorporated by reference in their entirety. This product, as exemplified by the QV-302 Pro model, for example, is able to use a microscope-type optical system to provide images of a workpiece at various magnifications, and move the stage as necessary to traverse the workpiece surface beyond the limits of any single video image. A single video image typically encompasses only a portion of the workpiece being observed or inspected, given the desired magnification, measurement resolution, and physical size limitations of such systems.
Machine vision inspection systems generally utilize automated video inspection. U.S. Pat. No. 6,542,180 teaches various aspects of such automated video inspection and is incorporated herein by reference in its entirety. As taught in the '180 patent, automated video inspection metrology instruments generally have a programming capability that allows an automatic inspection event sequence to be defined by the user for each particular workpiece configuration. This can be implemented by text-based programming, for example, or through a recording mode which progressively “learns” the inspection event sequence by storing a sequence of machine control instructions corresponding to a sequence of inspection operations performed by a user, or through a combination of both methods. Such a recording mode is often referred to as “learn mode” or “training mode.” Once the inspection event sequence is defined in “learn mode,” such a sequence can then be used to automatically acquire (and additionally analyze or inspect) images of a workpiece during “run mode.”
The machine control instructions including the specific inspection event sequence (i.e., how to acquire each image and how to analyze/inspect each acquired image) are generally stored as a “part program” or “workpiece program” that is specific to the particular workpiece configuration. For example, a part program defines how to acquire each image, such as how to position the camera relative to the workpiece, at what lighting level, at what magnification level, etc. Further, the part program defines how to analyze/inspect an acquired image, for example, by using one or more video tools such as edge/boundary detection video tools.
Video tools may be used manually to accomplish manual inspection and/or machine control operations. Also, their set-up parameters and operation can also be recorded during learn mode, in order to create automatic inspection programs, or “part programs”. Such tools may include, for example, edge/boundary detection tools, shape or pattern matching tools, dimension measuring tools, coordinate establishing tools, and the like. For example, such tools are routinely used in a variety of commercially available machine vision inspection systems, such as the QUICK VISION® series of vision systems and the associated QVPAK® software, discussed above.
Video edge/boundary detection tools available in QVPAK® software include, for example, Point tool, Box tool, Circle tool, and Arc tool (see QVPAK 3D CNC Vision Measuring Machine User's Guide, incorporated by reference above). Briefly, a Point tool generates (locates) a data point at the intersection of a single scan line on an image. A Box tool generates a series of parallel scan lines, each of which returns a data point where an edge feature is found. A Circle tool generates a series of radial scan lines, over 360 centered about an origin, each of which returns a point where an edge feature is found. An Arc tool generates a series of radial scan lines centered about an origin, each of which returns a point where an edge feature is found (useful for returning data points from a rounded corner, for example). Each of these tools may be used to automatically detect a particular edge/boundary feature in an image.
Proper operation of a video tool depends on correct settings of various machine, image acquisition, and video tool parameters that affect the image quality and the operation of the video tool. For example, for an edge/boundary detection video tool to locate a target edge/boundary in an image, the machine and image acquisition parameters must set a correct level of lighting/brightness, proper focusing, proper magnification, etc. Video tool parameters, for example for an edge-detection video tool, may include a region of interest of (i.e., the region within a video image that the video tool searches), an edge selector, a scan direction, and other parameters are that set to properly control the operations of the video tool to locate the edge/boundary feature that is desired be detected.
The currently available features and graphical user interface (GUI) controls for video tools, and particularly dimensional metrology video tools, are limited. Some existing video tools require relatively few “setup” actions by the user, but have the disadvantage that many of the resulting video tool parameters are set to default values that may be inappropriate in many situations. Other existing video tools allow the video tool parameters to be extensively adjusted or customized by the user, but have the disadvantage that they require several independent setup actions by the user. Video tools that overcome these and other disadvantages would be desirable.